Skip to main content ↑ ↓
Topic: Need Advice on Optimizing Artix Linux for High-Performance Computing (Read 326 times) previous topic - next topic
0 Members and 1 Guest are viewing this topic.

Need Advice on Optimizing Artix Linux for High-Performance Computing

Hello there,

I am relatively new to Artix Linux; though I have a background in using other Linux distributions like Ubuntu and Arch. I am working on setting up a system dedicated to high-performance computing (HPC) for data analysis and machine learning tasks. Given Artix's unique features and its reputation for being a lightweight and flexible distribution; I believe it could be an excellent fit for my needs.

Are there particular kernel configurations or patches that you would recommend to optimize for HPC workloads? Any specific tweaks that have worked well in your experience?

Since Artix uses runit; s6; or OpenRC instead of systemd; are there any service management tips or scripts that can help improve performance or relibility for high-intensity tasks?

I am planning to use software like TensorFlow; PyTorch; and various scientific libraries. Are there any best practices for managing these packages on Artix to ensure compatibility and performance? Is there a preferred source for these kinds of software?

What are some effective strategies for resource allocation and monitoring on Artix? Tools or techniques that are particularly well-suited for tracking CPU; GPU; and memory usage during intensive computations?

Also, I have gone through this post: https://forum.artixlinux.org/index.php/ccsp,4201.0.html which definitely helped me out a lot.

Any other advice for someone aiming to use Artix Linux in a high-performance computing environment? Personal experiences, potential pitfalls; or success stories would be greatly appreciated.

Thank you in advance for your help and assistance.